Automating PDF Resume Parsing with Airtable & OpenAI

Sorting and manually extracting key information from resumes and entering it into a database like Airtable is a repetitive and time-consuming task. This process, common in recruitment, involves opening each CV, identifying relevant details such as skills, contact information, and experience, and then copy-pasting them into the correct fields. This takes a lot of time and is prone to errors.

We implemented an automated solution using a combination of no-code and low-code tools:

• Airtable: Used to collect form submissions which include the resume/CV uploads. New applicant records are created automatically when a form is submitted.
• Zapier: Acts as the intermediary, triggering an automation whenever a new form is submitted in Airtable. Zapier takes the PDF CV from the Airtable record and exracts the text .
• OpenAI API (ChatGPT): Zapier sends the extracted CV text to the OpenAI API. A specific prompt instructs OpenAI to parse the resume and extract predefined values like "Skills," "Phone," "Email," "Links," "Education," "Biography," and "Experience".

This automated workflow ensures that once a resume is submitted, the information is automatically extracted and structured.

Implementing this automation produced positive outcomes:

• Automated Record Creation: New applicant records in Airtable are automatically populated with the applicant's name, role, a link to the form submission, and the PDF CV itself upon form submission.
• Auto Data Extraction: Key information like skills, phone number, email, education, and experience is automatically extracted from the CV by the OpenAI API.
• Database Updates: The extracted information is then automatically populated into the corresponding fields in the applicant's Airtable record, eliminating manual data entry.

This system ensures that candidate data is quickly and accurately captured and organized within Airtable.